It's Not Luck (6 page)

Stacey laughs dryly, “Déjà vu. We’ve been here before.”

“Yeah, but this time we are better off. Now we have more time, more than three months,” Bob adds sarcastically.

What they’re referring to is the time we worked together at Bearington, a plant that was a bottomless pit. We had exactly three months to turn it around, or else. . . . That’s when we met Jonah, and started to learn his Thinking Processes. That’s where we did the impossible; we actually turned it around in three months.

“Can we do it?” Don hesitantly asks.

I don’t think so. But if Bob and Stacey are willing to take the challenge, I’ll give it my all. In any event, what other choice do we have?

“Don, you haven’t worked with Alex long enough,” Stacey dismisses him, and then turns back to me. “Okay, Boss. What is the first step? Do you want a review of where we stand now?”

“Certainly,” I say, and look at Bob. “Go ahead, the floor is yours.”

He starts, “Remember the logical trees we constructed on how to handle distribution? Well, we have implemented them. Surprisingly enough we haven’t found any real problems. The central stock is established and we’ve started rearranging the regional stocks. So far, so good.”

“Good,” I say, “very good. So you straightened up production and now distribution. What’s next?”

“Engineering,” Bob replies confidently, “but I’m afraid it will take more than three months. Much more.”

“Not sales?” Don asks, sounding surprised.

“Not according to my analysis,” Bob says.

“How come?” Don asks. “Isn’t the market your constraint? I thought your improvements revealed enough excess capacity to double production. Isn’t your problem how to sell it?”

“Don, you’re right,” I interject, “Bob’s problem is how to increase sales, the constraint is in the market. But the fact that the constraint is in the market doesn’t mean that the core problem is in sales. The major reason preventing more sales might be anywhere in the company.”

“Yes, exactly,” Bob agrees. “And that’s why I think I should address engineering next.”

Turning to me he continues, “You see, in our business—cosmetics—if you want to increase sales, as a matter of fact if you want to just protect your sales, you must come up with new product lines. In the past a good product line was sufficient to sustain the company for four or five years. That’s not the case anymore. It’s become a rat race. I estimate that we will have to come out with a new product line every year.”

“To that extreme?” I ask.

“That’s on the optimistic side; probably it’s going to get worse. Anyhow, we have huge problems coming out with the products fast enough. Research is much too slow, and very unreliable. On top of it, even when they say that a product is complete, and we start to launch it in production, it turns out that what engineering calls complete is not what production calls complete. We start to produce a new product and a whole myriad of problems is immediately exposed.

“Currently, engineering spends more time on the production floor than in their labs. You can imagine this leads to some unpleasant surprises when we get to the market. We have huge problems synchronizing advertising the new lines with what the shops are actually offering.”

“So why did you bother with distribution?” Stacey asks.

He turns to her. “Stacey, when your finished goods pipeline has more than three months’ inventory, not taking into account what the shops are holding, do you know the meaning of launching a new product that’s replacing an existing one? Do you understand the magnitude of the write-offs?”

“I can imagine,” she replies. “All the inventory of the replaced product in the pipeline becomes obsolete. You must have a heck of a problem deciding when, and even if, you should launch a new product. Thank God I don’t have this chaotic situation to deal with. My products are relatively stable.”

“That’s what I claimed all along,” Bob laughs. “I should have gotten the pressure steam division, it’s much more in line with my character.”

Not just with his character; Bob even looks like a steam locomotive.

“So, Stacey, want to switch?”

“Bob, I have my own share of problems. Don’t offer it so casually, I might take you up on it.” We all laugh.

“I’d like to hear more about your distribution system,” Stacey says, and when I nod, she continues. “On one hand you have added central stocks, but on the other hand you have done this whole thing to reduce the pipeline. I want to understand it a little better.”

“No problem,” Bob says. “We are supplying a range of about six hundred and fifty different products to thousands of shops all over the country. In the past, we held about three months’ inventory, and it was never enough. Whenever a shop ordered—and remember they don’t order one item but a whole spectrum in one shot—we usually were out of some items. Only about thirty percent of the time could we ship a complete order. You can imagine how much it cost to ship the missing items later.

“With the new system, we are now able to respond to a shop within one day, with complete orders more than ninety percent of the time. Inventories are dropping fast; we expect to stabilize at roughly six weeks’ stock.”

“How did you achieve such a miracle?” Stacey is astonished.

“Simple,” Donovan replies, “we used to hold all the inventory in our regional warehouses.”

“Why?” I interrupt.

“The same old syndrome of local optima,” Bob answers.

“The plants were treated as profit centers. From the point of view of a plant manager, once he shipped the inventory, it left his jurisdiction, and it became distribution’s headache.”

“I bet the formal measurements reflected it,” Don says.

“Reflected, and enhanced it,” Bob agrees. “The minute that a product was shipped from the plant, on the books of the plant it was recorded as a sale. You can imagine that the minute the plant finished producing a product, that same day it was shipped to one of the regional warehouses.”

“Yes, naturally,” Don concurs. “So what are you doing differently?”

“Now we keep the stock at the plants themselves. At the regional warehouses we plan to have only what we’ve forecasted to sell in the next twenty days. That’s good enough because we now replenish each regional stock every three days.”

“I don’t get it at all,” Stacey admits. “But first, how do these changes lead to better fulfillment of orders with less stock. I don’t see the connection.”

“It’s simple,” I interrupt. “It’s all a matter of statistics. Our knowledge of what a shop sells of each item is very rough. One day they can sell ten units of something and the next day zero. Our forecast is based on averages.”

“That’s clear,” Stacey says.

“Now, which forecast will be more accurate?” I ask. “The forecast of the sales of one shop or the aggregated forecast of the sales of one hundred shops?”

“The aggregated forecast,” she answers.

“You are right, of course. The larger the number, the more accurate the aggregated forecast. The mathematical rule is that as we aggregate more and more shops the accuracy of the forecast improves in proportion to the square root of the number of shops that we aggregate. You see, when Bob moved the majority of his inventory from twenty-five regions into the plants themselves, his forecast became more accurate by a factor of five.”

“Alex, you with your statistics,” Bob cuts in. “I never understood them. Let me explain it in my way. Stacey, when you ship to a regional warehouse and you have, on average, three months’ inventory in the system, this inventory will be sold, on average, three months after the plant shipped it, right?”

“Provided that you have produced the right stuff in the first place, otherwise it will be even worse,” she agrees. “Now I see; as long as the plants have shipped immediately whatever they produced, their shipments to the warehouses were based on the forecast of what will be sold in that region three months down the road. Knowing the accuracy of such forecasts, especially when you are dealing with over six hundred products, I can imagine what was going on.”

“Don’t forget,” Bob adds, “that on top of six hundred and fifty products, I have twenty-five regional warehouses. This considerably adds to the mismatch.” We all nod, and Bob summarizes, “When a regional warehouse goes to fulfill a shop order, some items are always missing. At the same time, we do have these items; we have a lot of them, but in other warehouses. Now the madhouse starts. The warehouse manager is pressing the plants for immediate delivery, and if he can’t get it, he starts to call other warehouses. You won’t believe the amount of cross shipments between warehouses. It’s horrendous.”

“I can easily believe it,” Stacey says. “What else can you expect when the plants ship the goods three months in advance of consumption? You must end up with too much of one product in one place and too little in another. So I see what you’ve done; you wiped out local considerations and decided to hold the stock at the origin—at the plant.”

“Where the aggregation is the biggest,” I add. “Where the forecast is the most accurate.”

“But you still need the regional warehouses,” Stacey says thoughtfully.

“Yes,” Bob agrees, “since we want to respond quickly to the shops’ orders and cut shipping costs. Otherwise I’d have to ship each order to each shop directly from the plant. Federal Express would love it!”

“I see,” she says. “So how did you determine how much inventory you need to hold in each regional warehouse?”

“Ah-ha. That was the sixty-four-thousand-dollar question,” Bob beams. “Actually, it is quite simple. I just had to extrapolate from what we learned about buffering a physical constraint. Stacey, you’re probably as paranoid as I am about building inventory buffers before a bottleneck.”

“Yes, of course,” Stacey agrees.

“How do you decide on the size of a bottleneck’s buffer?”

“We figured that out together already in the Bearington plant,” she smiles. “The size of the buffer is determined by two factors: the expected consumption from it, and the expected replenishment time to it.”

“You got it,” Bob says, “and that is exactly what I’ve done with my distribution system. I treat the regional warehouses as buffers to the real physical constraint—the shops, the consumers. The size of each regional stock is determined, as you said, according to the consumption from it (by the shops it serves), and the replenishment time to it—which in this case is roughly one and a half times the larger of the shipping time from the plant, or the time interval between the shipments. You see, I use in distribution the rules we developed in production. Of course, with appropriate adjustments.”

“Carry on,” she says.

“Since I ship every three days, and for most regions the transportation time is about four days, I have to hold enough inventory in a regional warehouse to cover the next week’s actual sales. Bearing in mind that I really don’t know what exactly will be sold in the next four days, that the shops’ consumption is fluctuating all over the map, I have to be wary. Remember, the damage of not having the stock is bigger than the damage of holding more inventory. So, we decided to hold in each regional warehouse the equivalent of twenty days of average sales for the region.”

“I understand that you have to be a little paranoid, but it looks to me that inflating one week to three is not paranoia, it’s bordering on hysteria,” I say.

“You know me,” Bob laughs. “Nobody yet accused me of being hysterical.”

“So why so much? Why twenty days?”

“It’s because of the way the shops are ordering, in big bulk,” he answers. “I think that they got used to doing it because, in the past, we and our competitors were extremely unreliable. To guarantee that they don’t lose too many sales due to shortages, they don’t dare hold only what they need for the very near future. Some of them exaggerate to the extent that they order for the next six months. This, of course, causes spikes in the demand from our regional warehouses. Thank God that in each region there are so many shops that the weekly consumption is not totally erratic, otherwise even twenty days wouldn’t be sufficient.”

“If the shops would order according to what they actually sold, if they would just replenish,” Stacey thoughtfully says, “then your life would be much easier. Did you do anything to convince them to change?”

“Yes, of course,” Bob replies. “Our distribution managers sent them a letter, telling them we are willing to replenish to them even on a daily basis, but most are not taking advantage of this service. I guess that every change is slow, especially when we’re trying to change purchasing habits that have been in place for decades.”

“So how do you know if twenty days will be sufficient?” Stacey asks.

“This number is based not on experience, but on calculation,” Bob admits. “According to the current patterns of orders from the shops, twenty days will be sufficient to guarantee over ninety percent immediate response. Right now we are in transition. We already replenish the regional stock twice a week, ·but we haven’t yet totally drained the mountains of inventory that we still carry there. As a result, the current performance is too good; we can fulfill immediately over ninety-nine percent of the orders.

“There is no need to give such exceptional response. If in ninety percent of the cases the full order is immediately filled, we know that in the remaining ten percent of the cases the shops will wait a week for the residuals.